Bootstrapping a Change-Point Cox Model for Survival Data

2013/07/31 by Gongjun Xu, Xu, Gongjun, Bodhisattva Sen +3
Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #stat.ME

paper · pdf · doi:10.48550/arxiv.1307.8217

arxiv created 2013/07/31 · openalex publication_date 2013/07/31 · arxiv updated 2013/08/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper investigates the (in)-consistency of various bootstrap methods for making inference on a change-point in time in the Cox model with right censored survival data. A criterion is established for the consistency of any bootstrap method. It is shown that the usual nonparametric bootstrap is inconsistent for the maximum partial likelihood estimation of the change-point. A new model-based bootstrap approach is proposed and its consistency established. Simulation studies are carried out to assess the performance of various bootstrap schemes.

Citations

• Cox's Regression Model for Counting Processes: A Large Sample Study
• Change-point in stochastic design regression and the bootstrap

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